The present invention relates generally to the detection of oscillations of generators in power systems and, more particularly, to a method for accurately estimating properties of oscillation modes to help improve angular stability of power systems.
Major events in a power grid may cause growing angular oscillations between power plants or inter-connected control areas. If not detected and damped timely, oscillations may evolve into stability problems and trigger more outages. Accordingly, synchrophasors, e.g. phasor measurement units (PMUs), have been installed at key plants and substations to monitor oscillations in real time, and modal analysis has been used to analyze measurements provided by the PMUs.
Most existing approaches for modal analysis on measured signals apply spectral analysis-based approaches which are usually based on the Fast Fourier Transform (FFT) technique to identify a dominant oscillation mode, utilize Prony analysis, or Wavelet Transform (WT) to estimate damping, and perform cross-spectrum analysis to study the coherency and cross relationship between two signals about that mode in order to estimate the mode shape.
However, a problem with spectral analysis based approaches is that the accuracy of the estimated frequency or phase information is limited due to the nature of FFT algorithm. First, it has the spectral leakage issue when fed with a finite-length of signal. Second, it only outputs a finite number of discrete frequency components, which are predefined as frequency bins depending on a desired frequency resolution, due to computational complexity, and the actual frequency of the targeted mode in a signal of interest may be between two frequency bins, such that the accuracy of the estimated frequency is heavily influenced. Consequently, significant errors also exist in the other modal parameters. The situation is even worse when several oscillation modes of interest have close frequencies. Furthermore, when transient non-linear dynamics are non-negligible in measured signals due to the non-linear nature of a power system, the phase and frequency regarding an oscillation mode are actually floating, which also brings large errors to cross-spectrum based mode-shape analysis.
In damping estimation, Prony analysis has errors in estimating damping using signals with non-linear dynamics. WT-based techniques decompose a signal into a limited number of scales or frequency bands for signal decoupling. That nature limits the damping estimation accuracy.